Postdoctoral Research Fellow in Biomolecular / Chemical Data Science and Toxicology - UC Berkeley
We are looking for an individual with a background in biomolecular modeling and chemical informatics who is interested in chemical toxicology, data management, and analysis.
Our main project is developing integrated databases for large sets of biomolecular computational data and experimental or literature sources of chemical toxicology data.
This individual should have experience in Python programming, data science, and the use of large datasets. You will collaborate with a diverse scientific team to provide biomolecular modeling and cheminformatics expertise, data analysis and visualization, and integration of this data into appropriately designed database structures.
You will work under the supervision of Dr. Kathleen Durkin in the College of Chemistry and Dr. Martyn Smith in the School of Public Health, University of California, Berkeley.
Main Duties
- Perform biomolecular modeling on human protein receptors and ligands of toxicological concern.
- Develop integrated databases for large biomolecular computational and chemical toxicology data sets.
- Use and optimize diverse programming and other software tools for biomolecular computational data generation, analysis, visualization, and management.
- Use strong communication skills to interact with a diverse team.
- Contribute to figures, publications, and grant applications.
- Other duties as needed.
Education / Experience / Qualifications
- PhD in Computational Biology, Chemistry, Biochemistry, Bioinformatics, or a related field.
- Experience in biomolecular modeling such as molecular dynamics, docking, and high throughput small molecule screening, including workflow development and algorithmic design.
- Experience in SQL / NO-SQL databases and related languages.
- Expertise in Python, Django, Linux command line skills, and other development tools.
- Expertise in data analysis, including statistical techniques.
- Experience with Chemical toolkits (e.g., RDKit, scikit-learn), structural encoding, fingerprinting, and workflow environments (such as KNIME).
- Good understanding of Natural Language Processing techniques for semantic extraction, data structure, and modeling.
- Ability to work independently and have excellent organizational and problem-solving skills.
- Strong interpersonal skills and ability to work well with others.
- Excellent communication skills, both written and oral.
Applicants should send a PDF (or PDFs) containing a cover letter, a CV (including DOIs or other URLs to publications), and names / emails of 3 potential references to mgcf-hire,berkeley.
edu. Background Check : Employment is contingent on a satisfactory pre-employment background check.
Benefits - University of California offers outstanding benefits to eligible employees and their dependents, including health, life, dental, and vision insurance.
Salary scales are here : https : / / vspa.berkeley.edu / postdoc-compensation, and the level will be based on experience.
University of California is committed to diversity and is an equal opportunity / equal access employer.
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